Principal Data Architect

RESPONSIBILITIES

• Data Ingestion: Design and build the pipelines that bring data in for feature engineering and machine learning
• Feature Engineering: Use your knowledge of healthcare data, statistics, and data science to create features with real predictive power
• Feature Extraction and Selection: Use techniques like clustering, text analytics, and PCA to find the most useful signals while preserving the meaning in the original data, so models stay accurate and scale well
• Exploratory Data Analysis: Explore the data to find patterns, trends, and relationships, and use what you learn to match features with the right modeling approach
• Model Development: Experiment with statistical and machine learning methods to build, tune, and optimize predictive models that fit the use case
• Deployment: Ship production code that follows engineering best practices
• Documentation and Communication: Document your work and share your approach, insights, and solutions with technical and non-technical audiences
• Monitoring: Build and maintain the pipelines and processes that keep our enterprise data science products running smoothly
• Quality and Integrity: Keep data and outputs accurate and reliable from start to finish
• Collaboration: Partner with stakeholders, data scientists, data engineers, and product managers to build and deliver great data products

QUALIFICATIONS

• Experience: 6+ years working across data science and machine learning (for the Lead level)
• Core Languages: Expert-level SQL and Python
• Data Types: Hands-on work with both structured and unstructured data, such as tables, text, images, and video
• Databases: Experience with both relational (SQL) and non-relational (NoSQL) databases
• Data Processing: Familiarity with ETL and data processing tools like Apache Spark
• Visualization and Monitoring: Experience using tools to visualize data and monitor its health
• Engineering Practices: Comfort with modern software practices like automated testing and CI/CD
• Containers: Experience with Docker
• Cloud: Experience deploying to GCP or another cloud platform

BONUS EXPERIENCE

• Consulting or Professional Services Background
• Domain Knowledge of Healthcare Data
• Knowledge of Healthcare Protocols such as HL7, FHIR, DICOM